Relative contributions of arterial stiffness to cardiovascular disease risk score in Chinese women in framingham and China-PAR model.

Background: Arterial stiffness played an important role in the development of cardiovascular disease (CVD) events. The aim of this study was to verify the relative importance of arterial stiffness for different CVD risk scores in a large sample of Chinese women. Methods: We measured arterial velocity pulse index (AVI) and CVD risk scores in 2220 female participants (mean age 57 years). Framingham Risk Score (FRS), and the prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) were used to estimate CVD risk, respectively. The relationships between AVI and risk scores were investigated by linear regressions and restricted cubic spline (RCS) analysis. To determine the relative importance of AVI in predicting CVD risk scores, random forest analysis was used. Results: There was a significant positive correlation between AVI and FRS, China-PAR in all subgroup groups stratified by age, blood pressure and BMI. AVI showed higher importance in predicting CVD risk scores in FRS model, compared with these traditional risk factors. In China-PAR model, although AVI was not as predictive as SBP, it had better predictive power than many known risk factors such as lipids. Furthermore, AVI had significant J-shaped associations both with FRS and China-PAR scores. Conclusions: AVI was significantly associated with CVD risk score. In FRS and China-PAR model, AVI showed relatively high importance in predicting CVD risk scores. These findings may support the use of arterial stiffness measurements in CVD risk assessment.

Chloroplast-inspired Scaffold for Infected Bone Defect Therapy: Towards Stable Photothermal Properties and Self-Defensive Functionality.

Bone implant-associated infections induced by bacteria frequently result in repair failure and threaten the health of patients. Although black phosphorus (BP) material with superior photothermal conversion ability is booming in the treatment of bone disease, the development of BP-based bone scaffolds with excellent photothermal stability and antibacterial properties simultaneously remains a challenge. In nature, chloroplasts cannot only convert light into chemical energy, but also hold a protective and defensive envelope membrane. Inspired by this, a self-defensive bone scaffold with stable photothermal property is developed for infected bone defect therapy. Similar to thylakoid and stroma lamella in chloroplasts, BP is integrated with chitosan and polycaprolactone fiber networks. The mussel-inspired polydopamine multifunctional "envelope membrane" wrapped above not only strengthens the photothermal stability of BP-based scaffolds, but also realizes the in situ anchoring of silver nanoparticles. Bacteria-triggered infection of femur defects in vivo can be commendably inhibited at the early stage via these chloroplast-inspired implants, which then effectively promotes endogenous repair of the defect area under mild hyperthermia induced by near-infrared irradiation. This chloroplast-inspired strategy shows outstanding performance for infected bone defect therapy and provides a reference for the functionality of other biomedical materials.

Self-Organized Spatiotemporal Mineralization of Hydrogel: A Simulant of Osteon.

Nature creates fascinating self-organized spatiotemporal patterns through the delicate control of reaction-diffusion dynamics. As the primary unit of cortical bone, osteon has concentric lamellar architecture, which plays a crucial role in the mechanical and physiological functions of bone. However, it remains a great challenge to fabricate the osteon-like structure in a natural self-organization way. Taking advantage of the nonequilibrium reaction in hydrogels, a simple mineralization strategy to closely mimic the formation of osteon in a mild physiological condition is developed. By constructing two reverse concentration gradients of ions from periphery to interior of cylindrical hydrogel, spatiotemporal self-organization of calcium phosphate in concentric rings is generated. It is noteworthy that minerals in different layers possess diverse contents and crystalline phases, which further guide the adhesion and spread of osteoblasts on these patterns, resembling the architecture and cytological behavior of osteon. Besides, theoretical data indicates the predominate role of ion concentrations and pH values of solution, in good accordance with experimental results. Independent of precise instruments, this lifelike method is easily obtained, cost-efficient, and effectively imitates the mineral deposition in osteon from a physiochemical view. The strategy may be expanded to develop other functional material patterns via spatiotemporal self-organization.

Chemically Grafted Nanozyme Composite Cryogels to Enhance Antibacterial and Biocompatible Performance for Bioliquid Regulation and Adaptive Bacteria Trapping.

Excessive biofluid and infection around wounds hinder wound healing. However, conventionally antibacterial wound dressings cannot simultaneously achieve effective biofluid control and intelligent infection treatment, tending to overhydrate wounds and develop drug-resistant bacteria due to the limitations of antibacterial components and material structures. The design of a nanozyme composite cryogel with interconnected macroporous structures, excellent designability, and lower chance of drug-resistance is greatly needed. Herein, Fe-MIL-88NH2 nanozyme is grafted to glycidyl methacrylate functionalized dialdehyde chitosan via Schiff base reaction, and acryloyl Pluronic 127 (PF127-DA) is used as a cross-linking agent to fabricate nanozyme composite cryogels (CSG-MX) as a wound dressing to enhance antibacterial and biocompatible performance for biofluid management and wound infection therapy. CSG-MX has great hydrophilicity, acid-enhanced positive charge, pH-responsive release, rebinding of nanozymes, and excellent peroxidase and oxidase mimicry activity (generation of •OH and O2•- radicals). Notably, due to the negative potential of bacteria, the impact of infection on pH value, and the enzyme-like activity as well as the reversible release of nanozymes influenced by pH, CSG-MX can achieve intelligently adaptive trapping and killing of bacteria. CSG-MX has enormous potential to be a next-generation wound dressing for biofluid management and bacterial infection treatment in the clinic.

Overall Structure Construction of an Intervertebral Disk Based on Highly Anisotropic Wood Hydrogel Composite Materials with Mechanical Matching and Buckling Buffering.

Natural intervertebral disks (IVDs) exhibit distinctive anisotropic mechanical support and dissipation performances due to their well-developed special microstructures. As the intact IVD structure degrades, the absence of function will lead to severe backache. However, the complete simulation for the characteristic structure and function of native IVD is unattainable using current methods. In this work, by overall construction of the two-phase structure of native IVD (extraction of the naturally aligned cellulose framework and in situ polymerization of the nanocomposite hydrogel), a complete wood framework IVD (WF-IVD) is manufactured containing elastic nanocomposite hydrogel-based nucleus pulposus (NP) and anisotropic wood cellulose hydrogel-based annulus fibrosus (AF). In addition to the imitation and construction of the natural structure, WF-IVD also achieves favorable mechanical matching and good biocompatibility and possesses unique mechanical buckling buffer characteristics owing to the aligned fiber bundles. This study offers a promising strategy for the mimicking and construction of complex native tissues.

Automated Machine-Learning Framework Integrating Histopathological and Radiological Information for Predicting IDH1 Mutation Status in Glioma.

Diffuse gliomas are the most common malignant primary brain tumors. Identification of isocitrate dehydrogenase 1 (IDH1) mutations aids the diagnostic classification of these tumors and the prediction of their clinical outcomes. While histology continues to play a key role in frozen section diagnosis, as a diagnostic reference and as a method for monitoring disease progression, recent research has demonstrated the ability of multi-parametric magnetic resonance imaging (MRI) sequences for predicting IDH genotypes. In this paper, we aim to improve the prediction accuracy of IDH1 genotypes by integrating multi-modal imaging information from digitized histopathological data derived from routine histological slide scans and the MRI sequences including T1-contrast (T1) and Fluid-attenuated inversion recovery imaging (T2-FLAIR). In this research, we have established an automated framework to process, analyze and integrate the histopathological and radiological information from high-resolution pathology slides and multi-sequence MRI scans. Our machine-learning framework comprehensively computed multi-level information including molecular level, cellular level, and texture level information to reflect predictive IDH genotypes. Firstly, an automated pre-processing was developed to select the regions of interest (ROIs) from pathology slides. Secondly, to interactively fuse the multimodal complementary information, comprehensive feature information was extracted from the pathology ROIs and segmented tumor regions (enhanced tumor, edema and non-enhanced tumor) from MRI sequences. Thirdly, a Random Forest (RF)-based algorithm was employed to identify and quantitatively characterize histopathological and radiological imaging origins, respectively. Finally, we integrated multi-modal imaging features with a machine-learning algorithm and tested the performance of the framework for IDH1 genotyping, we also provided visual and statistical explanation to support the understanding on prediction outcomes. The training and testing experiments on 217 pathologically verified IDH1 genotyped glioma cases from multi-resource validated that our fully automated machine-learning model predicted IDH1 genotypes with greater accuracy and reliability than models that were based on radiological imaging data only. The accuracy of IDH1 genotype prediction was 0.90 compared to 0.82 for radiomic result. Thus, the integration of multi-parametric imaging features for automated analysis of cross-modal biomedical data improved the prediction accuracy of glioma IDH1 genotypes.

A facile strategy to construct silk fibroin based GTR membranes with appropriate mechanical performance and enhanced osteogenic capacity.

Periodontitis is one of the most common inflammatory diseases that can eventually cause tooth loss in adults. For the successful regeneration of periodontal tissue, one of the most feasible ways is the development of functional guided tissue regeneration (GTR) membranes with improved osteogenic capability. Here, we fabricated electrospun silk fibroin (SF) nanofibrous membranes and designed a low-cost and eco-friendly strategy to modify the SF matrix via tannic acid (TA). In this process, the conformational transition of SF protein triggered by TA made a remarkable improvement in mechanical properties of the SF membranes. More importantly, TA could induce biomimetic mineralization and in situ growth of hydroxyapatite (HAp) on the surface of the SF nanofibrous matrix. Cell experiments demonstrated that TA-coated SF nanofibrous membranes after mineralization could facilitate the proliferation and osteo-differentiation of MC3T3 cells. Considering the effectivity and methodological simplicity, this TA-mediated modification is a promising method to prepare SF-based GTR membranes with better mechanical performance and osteogenic function.

Biomimetic synthesis of chondroitin sulfate-analogue hydrogels for regulating osteogenic and chondrogenic differentiation of bone marrow mesenchymal stem cells.

As a typical representative of crucial glycosaminoglycans (GAGs), chondroitin sulfate (CS) with sulfonated polysaccharide in structures extensively exists in the extracellular matrix (ECM) and exhibits peculiar bioactivity on the regulation of cells behaviors and fates (e.g. proliferation and differentiation) in organisms. Nevertheless, some intrinsic disadvantages of natural CS mainly ascribe to the intricate structure and inhomogeneous composition (especially the uncontrollable sulfonate degrees), resulting in overt restrictions on its physiological functions and applications. Although recent bionic synthesis of artificial GAGs analogues at the molecular level have already provides an efficient strategy to reconstruct GAG for regulating the cellular behaviors and fates, it still remains great challenges to rationally design and synthesize GAGs analogues with special composition and structure for precisely mimicking ECM. Simultaneously, the relevant regulation process of GAG analogues on cell fate needs to be further studied as well. Herein, chondroitin sulfate-analogue (CS-analogue) hydrogels with diverse contents of saccharide and sulfonate units in the networks were fabricated through photo-polymerization and then characterized by Fourier transform infrared (FT-IR) spectroscopy, zeta potential and scanning electron microscope (SEM). Additionally, CS-analogue hydrogels with proper mechanical properties exhibited favorable swelling, degradation performance and prominent cytocompatibility. According to cell cultivation results, CS-analogue hydrogel with a certain proportion of saccharide and sulfonate units presented preferable promotion on the adhesion, spreading, proliferation and differentiation of bone marrow mesenchymal stem cells (BMSCs), shedding light on the significance of saccharide and sulfonate units in regulating cell behaviors. Furthermore, BMSCs cultivated with CS-analogue hydrogels under different culture conditions were also systematically investigated, revealing that with the help of cultivation environment CS-analogue hydrogels owned the remarkable capacity of directing either chondrogenic or osteogenic differentiation of BMSCs. Therefore, it is envisioned that versatile CS-analogue hydrogels would have promising application prospects in the biomedical and clinical fields.

Programmed antibacterial and mineralization therapy for dental caries based on zinc-substituted hydroxyapatite/ alendronate-grafted polyacrylic acid hybrid material.

The domination of cariogenic bacteria in dental plaque biofilms is the primary cause of dental caries. In view of this, for the purpose of an effective treatment of dental caries, it is of great importance to inhibit the activity of acidogenic bacteria and promote the remineralization of damaged teeth simultaneously. However, the expensive antibacterial agents and poor mineralization ability of materials limit the practical applications. Biomineralization regulated by non-collagenous proteins (NCPs) gives hints to combine the remineralization ability of NCPs with accessible antibacterial property effectively. In this work, we propose a programmed antibacterial and remineralization strategy for the therapy of dental caries based on zinc-substituted hydroxyapatite/ alendronate-grafted polyacrylic acid hybrid nanoneedles (ZHA@ALN-PAA). This hybrid material dissolves in the acidic caries environment and regulate the pH to nearly neutral (6.5). Abundant calcium/ phosphate ions are supplemented and the ALN-PAA embedded in it has also been released, which assists the biomineralization on tooth defect. It has been revealed that the inhibition ratio of ZHA@ALN-PAA against Streptococcus mutans is the highest (11.25 folds that of HA), which originates from the highest zinc ions released (132.9 mg/L). Besides, the interspace of etched enamel is fully filled with regenerated nanorods and the surface microhardness (SMH) is significantly improved (3.68 folds that of etched enamel) after only 3 days of mineralization in vitro. This strategy developed here is simple and cost-effective, which can be referred to design the effective anti-caries materials applied for clinic treatment and daily oral care.

Wood-Derived Hybrid Scaffold with Highly Anisotropic Features on Mechanics and Liquid Transport toward Cell Migration and Alignment.

Fantastic structures in nature have inspired much incredible research. Wood, a typical model of anisotropy and hierarchy, has been widely investigated for its mechanical properties and water extraction abilities, although applications in biological areas remain challenging. Delignified wood composite with in situ deposited hydroxyapatite (HAp) and infiltrated polycaprolactone (PCL) is hereby fabricated in an attempt to mimic natural bone. The inherent structure and properties of wood are carefully preserved during the fabrication, showing anisotropic mechanical properties in the radial direction (420 MPa) and longitudinal direction (20 MPa). In addition, it also performs directional liquid transport, effectively inducing the migration and alignment of cells to simulate the uniform seeding behavior of various cells in natural bone. Moreover, the synergistic effect of blended HAp and PCL largely promotes cell proliferation and osteogenic differentiation, providing a promising candidate for bone regeneration materials.

Machine Learning Models for Multiparametric Glioma Grading With Quantitative Result Interpretations.

Gliomas are the most common primary malignant brain tumors in adults. Accurate grading is crucial as therapeutic strategies are often disparate for different grades and may influence patient prognosis. This study aims to provide an automated glioma grading platform on the basis of machine learning models. In this paper, we investigate contributions of multi-parameters from multimodal data including imaging parameters or features from the Whole Slide images (WSI) and the proliferation marker Ki-67 for automated brain tumor grading. For each WSI, we extract both visual parameters such as morphology parameters and sub-visual parameters including first-order and second-order features. On the basis of machine learning models, our platform classifies gliomas into grades II, III, and IV. Furthermore, we quantitatively interpret and reveal the important parameters contributing to grading with the Local Interpretable Model-Agnostic Explanations (LIME) algorithm. The quantitative analysis and explanation may assist clinicians to better understand the disease and accordingly to choose optimal treatments for improving clinical outcomes. The performance of our grading model was evaluated with cross-validation, which randomly divided the patients into non-overlapping training and testing sets and repeatedly validated the model on the different testing sets. The primary results indicated that this modular platform approach achieved the highest grading accuracy of 0.90 ± 0.04 with support vector machine (SVM) algorithm, with grading accuracies of 0.91 ± 0.08, 0.90 ± 0.08, and 0.90 ± 0.07 for grade II, III, and IV gliomas, respectively.

Identification of effective combinatorial markers for quality standardization of herbal medicines.

Quality standardization of herbal medicines (HMs) is an important task with great challenges. Selection of abundant compounds as markers is currently a major approach for the quality control of HMs; however, such marker compounds are irrelevant to the bioactivities in many cases. Taking Lycoridis Radiatae Bulbus (LRB) as an example, we proposed a universal strategy to identify the effective combinatorial markers (ECMs) that are representative of the bioactivities of HMs, and took them as chemical markers for quality standardization. Fingerprinting and quantification were employed to find out the common components in various batches of medicines. The contribution of each common compound to the overall bioactivity was determined through fingerprint-bioactivity modeling, which based on the absolute quantification of each compound and the acetylcholinesterase (AChE) inhibitory activity of LRB. Two most effective compounds, ungerimine and galanthamine, were therefore proposed as ECMs. Interestingly, these two compounds could synergistically inhibit AChE. This approach demonstrated its strong advantage of the bioactivity relevant quality assessment when compared with conventional methods. And the success of applying this ECMs-based method to the quality assessment of unknown LRB samples proved that our approach was reliable and reproducible. In conclusion, this approach is not only useful for the bioactivity relevant quality control of HMs but also helpful for the discovery of ECMs as new drug candidates.

[Application of mass spectrometry-based chromatographic technologies in the diagnosis of Alzheimer's disease].

With the rapid growth of the elderly population in the world, the incident number of Alzheimer's disease (AD) is also increasing year by year. AD has become "the third biggest killer" to human health besides cardiovascular and cerebrovascular diseases and cancers. The diagnosis and treatment of diseases are of equally significance. Generally, the diagnosis of AD relies upon the typical clinical features, neuroimaging techniques, and the detection of disease-related biomarkers. In recent years, proteomics and mass spectrometry technology have developed rapidly, which can be used to find specific disease-related proteins as biomarkers for early diagnosis. This review focused on the proteomics-based screening of diagnostic biomarkers and the mass spectrometry-based chromatographic technologies applied in the diagnosis of AD. 34 references are reviewed.